Overview
Explores how granular computing plays a significant role in advancing machine learning towards in-depth processing of big dataIntroduces the main characteristics of big data, i.e. the five Vs--Volume, Velocity, Variety, Veracity, and Variability Presents popular types of traditional machine learning in terms of their key features and limitations in the context of big data Discusses the need for and different uses of granular computing based machine learning Presents several case studies of big data by using biomedical data and sentiment data, demonstrating recent advances Stresses the theoretical significance, practical importance, methodological impact, and philosophical aspects
- | Author: Han Liu
- | Publisher: Springer
- | Publication Date: Nov 23, 2017
- | Number of Pages: 113 pages
- | Binding: Hardback or Cased Book
- | ISBN-10: 331970057X
- | ISBN-13: 9783319700571
